This article introduces a novel Atmosphere Clouds Model Optimization algorithm (ACMO), which is inspired by the generation behavior, move behavior and spread behavior of clouds in the natural world. As
the global search method of ACMO algorithm, the reverse search method composed by the move behavior and spread behavior of clouds disperses the whole population to the search space. This method can enhance
the diversity of population; the generation behavior is mainly used to search in the vicinities of current global optimal, keeping the convergence of ACMO algorithm. And the proposed algorithm has been tested on a set
of multimodal functions in comparison with Particle Swarm Optimization algorithm (PSO) and Genetic Algorithm (GA). The results demonstrate that the proposed algorithm has a certain advantage in solving multimodal
functions.